[Status and perspective of soil fauna eco-geography in China]. / ä¸­å›½åœŸå£¤åŠ¨ç‰©ç”Ÿæ€åœ°ç†å­¦ç ”ç©¶çŽ°çŠ¶ä¸Žå±•æœ›.

As regulators of the surface land processes, soil fauna communities are the vital foundations for healthy terrestrial ecosystems. Soil fauna have been studied in China for more than 70 years. Great progresses have been achieved in exploring soil fauna species composition and geographical distribution patterns. Soil fauna eco-geography, as a bridge between soil fauna geographic patterns and ecosystem services, has a new development opportunity with the deep recognition of soil fauna ecological functions. Soil fauna eco-geography research could be partitioned into four dimensions including the spatio-temporal patterns of: 1) the apparent characteristics of soil fauna community, such as species composition, richness and abundance; 2) the intrinsic characteristics of soil fauna community, such as dietary and habits; 3) soil fauna-related biotic and abiotic interactions especially those indicating drivers of soil fauna community structure or shaping the roles of soil fauna in ecosystems; and 4) soil fauna-related or -regulated key ecological processes. Current studies focus solely on soil fauna themselves and their geographical distributions. To link soil fauna geography more closely with ecosystem services, we suggested that: 1) converting the pure biogeography studies to those of revealing the spatio-temporal patterns of the soil fauna-related or regulated key relationships and ecological processes;2) expanding the temporal and spatial scales in soil fauna geographical research;3) exploring the integrated analysis approach for soil fauna-related data with multi-scales, multi-factors, and multi-processes;and 4) establishing standard reference systems for soil fauna eco-geographical researches. Hence, the change patterns of ecological niche of soil fauna communities could be illustrated, and precision mani-pulations of soil fauna communities and their ecological functions would become implementable, which finally contributes to ecosystem health and human well-being.

Vegetation restoration altered the soil organic carbon composition and favoured its stability in a Robinia pseudoacacia plantation.

Soil organic carbon (SOC) stabilization is vital for the mitigation of global climate change and retention of soil carbon stocks. However, there are knowledge gaps on how SOC sources and stabilization respond to vegetation restoration. Therefore, we investigated lignin phenol and amino sugar biomarkers, SOC physical fractions and chemical structure in one farmland and four stands of a Robinia pseudoacacia plantation. We observed that the content of SOC increased with afforestation, but the different biomarkers had different contributions to SOC. Compared to farmland, the contribution of lignin phenols to SOC decreased in the plantations, whereas there was no difference among the four stand ages, likely resulting from the balance between increasing lignin derivation input and increasing lignin degradation. Conversely, vegetation restoration increased the content of microbial necromass carbon (MNC) and the contribution of MNC to SOC, mainly because microbial residue decomposition was inhibited by decreasing the activity of leucine aminopeptidase, while microbial necromass preservation was promoted by adjusting soil variables (soil water content, clay, pH and total nitrogen). In addition, vegetation restoration increased the particulate organic carbon (POC), mineral-associated organic carbon (MAOC) pools and the O-alkyl C intensify. Overall, vegetation restoration affected SOC composition by regulating lignin phenols and microbial necromass and also altered SOC stabilization by increasing the physically stable MAOC pool during late afforestation. The results of this study suggest that more attention should be given to SOC sequestration and stability during late vegetation restoration.

Logistics Path Decision Optimization Method of Fresh Product Export Cold Chain Considering Transportation Risk.

The cold chain logistics route of fresh product export is characterized by large quantity and complexity, which is prone to cause transportation risks of different degrees in the process of fresh product export transportation and affects the decision-making effect of the cold chain logistics route. Therefore, in order to improve the ability of cold chain logistics route planning and shorten the transportation time, an optimization method of fresh product export cold chain logistics route decision considering transportation risk was proposed. This paper analyzes the basic characteristics and classification of cold chain logistics by means of risk quantification and uses the K-nearest neighbor algorithm to predict the risk of traffic congestion, so as to shorten the transportation time. Ahp process is used to construct a risk factor judgment matrix and determine the index weight of risk factors, so as to reduce the error of path planning. A genetic algorithm is introduced to construct the optimal decision function of the cold chain logistics route of new product export and realize the optimization of cold chain logistics route decision of fresh product export. Experimental results show that the method presented in this paper can effectively improve the decision-making effect of cold chain logistics route and select the shortest and most smooth transportation path to complete logistics distribution. The decision-making accuracy of the route decision effect is 90%, and the transportation time is 31.45 min, which has certain feasibility and applicability.

A Method for Evaluating the Green Economic Efficiency of Resource-Based Cities Based on Neural Network Improved DEA Model.

In this study, we use BP neural network to improve the DEA model to conduct in-depth research and analysis on the method of green economic efficiency evaluation of resource-based cities. The traditional DEA cannot make ranking and analysis of effective units, which affects the accuracy of empirical analysis. Accordingly, the BP-DEA model is introduced to further conduct a comparative eco-efficiency analysis of relatively effective provinces. In this study, the optimal inputs and outputs are calculated by DEA, and further, the BP neural network is used to fit the functional relationship between the optimal inputs and outputs, and by adding variables, the trained neural network can be used for the prediction of the optimal outputs. In this study, the BP-DEA model is used to empirically investigate the temporal evolution trend, spatial differences, and efficiency differences in eco-efficiency. Meanwhile, breaking through the limitation that DEA can only calculate regional efficiency values, this study combines the Malmquist index to compare and decompose the eco-efficiency of different provinces to analyze the sources of total factor productivity changes. The results show that the method can clarify the gap between the actual operation of each indicator and the reference point; it can identify how much room for improvement still needs to be made for each indicator, and it can also determine whether each city should be rewarded or penalized and its specific amount. Finally, based on the evaluation of eco-efficiency and the main constraints, corresponding policy recommendations are proposed. Finally, based on the evaluation results of the BP-DEA method, this study analyzes the overall efficiency improvement of cities in the two study areas in three dimensions: urbanization construction, ecology, and economic development put forward seven types of urban efficiency improvement and propose targeted urban development suggestions according to regional characteristics.

Dysfunction of collagen synthesis and secretion in chondrocytes induced by wisp3 mutation.

Wisp3 gene mutation was shown to cause spondyloepiphyseal dysplasia tarda with progressive arthropathy (SRDT-PA), but the underlying mechanism is not clear. To clarify this mechanism, we constructed the wild and mutated Wisp3 expression vectors and transfected into human chondrocytes lines C-20/A4; Wisp3 proteins subcellular localization, cell proliferation, cell apoptosis, and Wisp3-mediated gene expression were determined, and dynamic secretion of collagen in transfected chondrocytes was analyzed by (14)C-proline incorporation experiment. Mutated Wisp3 protein increased proliferation activity, decreased apoptosis of C-20/A4 cells, and aggregated abnormally in cytoplasm. Expression of collagen II was also downregulated in C-20/A4 cells transfected with mutated Wisp3. Wild type Wisp3 transfection increased intracellular collagen content and extracellular collagen secretion, but the mutated Wisp3 lost this function, and the peak phase of collagen secretion was delayed in mutated Wisp3 transfected cells. Thus abnormal protein distribution, cell proliferation, collagen synthesis, and secretion in Wisp3 mutated chondrocytes might contribute to the pathogenesis of SEDT-PA.